铁路网列车再生能量利用的鲁棒混合优化最优化模型
A Robust Mixed Integer Optimization Model to Utilize Regenerative Energy of Trains in a Railway Network
摘要：
本文提出了一个鲁棒混合整数最优化模型，以利用铁路网中列车产生的再生制动能量。电动训练在制动期间产生再生能量，该再生能量在现有技术中经常损失。为了利用这种能量，我们计算出一个时间表，该时间表使合适的训练对的制动和加速阶段之间的总重叠时间最大化，使得制动训练的再生能量可以转移到合适的加速阶段。我们将我们的最优化模型应用于不同的情况下，铁路网络的时间跨度为6小时。对于每一个实例，我们的模型都能很快找到最佳时间表（最大运行时间为86.64秒）。与现有的时间表相比，我们观察到每种情况下可再生能源的利用率都有显着提高。
英文摘要：
In this paper we present a robust mixed integer optimization model to utilize regenerative braking energy produced by trains in a railway network. An electric train produces regenerative energy during braking, which is often lost in present technology. To utilize this energy we calculate a timetable which maximizes the total overlapping time between the braking and accelerating phases of suitable train pairs, so that the regenerative energy of a braking train can be transferred to a suitable accelerating one. We apply our optimization model to different instances of a railway network for a time horizon spanning six hours. For each instance, our model finds an optimal timetable very quickly (largest running time being 86.64 seconds). Compared to the existing timetables, we observe significant increase in utilization of regenerative energy for every instance.
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